Leveraging AI to Capture Missed Early Payment Discounts

Sherry: Hello, and welcome to all our viewers on CFO Insights. I am Sherry, a financial technology consultant at Hyperbots, and I'm very excited to have Shaun Walker here with me, who is a seasoned internal audit leader with a wealth of experience in driving risk management, compliance, and governance initiatives across diverse industries. Thank you so much for joining us today, Shaun. Today we'll be discussing leveraging AI to capture missed early payment discounts. To get us started, why is it challenging for companies to manually monitor early payment discounts?

Shaun Walker: Tracking early payment discounts is difficult because vendors offer varied discount terms across hundreds or even thousands of invoices. Reviewing each invoice, purchase order, and vendor record to compute discount values, compare them to the cost of capital, and make timely decisions is highly time-consuming and prone to error.

Sherry: What types of discount terms typically vary among vendors?

Shaun Walker: Discount terms vary in both percentage and timing. For example, one vendor might offer a 2% discount if paid within 10 days, while another may offer a 1% discount if paid within 15 days. These differences require careful interpretation to determine which discount offers the best financial benefit.

Sherry: How do missed early payment discounts impact a company's financial performance?

Shaun Walker: Missing early payment discounts can result in significant savings. For instance, if a company misses a 2% discount on a $500,000 invoice, it loses $10,000. Over time, these missed opportunities can negatively affect cash flow and reduce overall profitability.

Sherry: In continuation of that, what analytical challenges are involved in evaluating discount opportunities?

Shaun Walker: Evaluating discount opportunities requires complex analytics, extracting discount terms from invoices and POs, computing potential savings, and comparing these with the company's cost of capital. This process demands integration of data from multiple sources and precise calculations, which can be tedious and error-prone when done manually.

Sherry: To avoid everything we just talked about, how does Hyperbots’ Payment AI Copilot address these challenges?

Shaun Walker: Hyperbots automate the entire process. It reads, understands, and interprets discount terms from invoices, POs, and vendor records. It creates a comprehensive schedule and real-time recommendations. This automation ensures that every discount opportunity is captured and evaluated, reduces manual errors, and frees up valuable time for strategic decision-making.

Sherry: How does this AI continuously update its recommendations for discount opportunities?

Shaun Walker: It continuously analyzes incoming data from updated invoices, POs, and vendor records in real-time. It also compares new information with historical trends and the cost of capital to refine its recommendations.

Sherry: What overall benefits have you seen from automating the monitoring of early payment discount opportunities?

Shaun Walker: Automating discount monitoring streamlines payment processes, reduces manual errors, and ensures no discount opportunities are missed. This leads to significant cost savings, improved cash flow management, and enhanced vendor relationships.

Sherry: Thank you so much for joining us today, Shaun. It's always an insightful conversation when you are on CFO Insights with us.

Shaun Walker: Absolutely, thanks for having me.